Texture representation of SAR sea ice imagery using multi-displacement co-occurrence matrices

Leen Kiat Soh, Costas Tsatsoulis

Research output: Contribution to conferencePaper

4 Scopus citations

Abstract

In this paper, we describe multi-displacement co-occurrence matrices for representing sea ice textures of SAR imagery. Our design of co-occurrence matrices captures local relationships among neighboring pixels and global links among distant pixels, an advantage over other existing versions of co-occurrence matrices. As a result, it can adequately represent micro textures, such as grainy details, and macro textures, such as patchy blocks. We have conducted experiments to compare our multi-displacement co-occurrence matrices with other existing versions using Bayesian linear discrimination. We have found that our design is the most texturally representative in terms of classification accuracies in both training and test datasets. In addition, we have applied this design to sea ice texture analysis which includes detection and localization, and subsequent image-texture mapping.

Original languageEnglish (US)
Pages112-114
Number of pages3
Publication statusPublished - Jan 1 1996
EventProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4) - Lincoln, NE, USA
Duration: May 28 1996May 31 1996

Other

OtherProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4)
CityLincoln, NE, USA
Period5/28/965/31/96

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ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

Cite this

Soh, L. K., & Tsatsoulis, C. (1996). Texture representation of SAR sea ice imagery using multi-displacement co-occurrence matrices. 112-114. Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, .